Clustering Algorithms

Learn clustering techniques that group similar data points together, helping in customer segmentation, anomaly detection, and exploratory analysis.

📄️ K-Means

Grouping data into K clusters by minimizing within-cluster variance.

Understanding Agglomerative clustering, Dendrograms, and linkage criteria.

Discovering clusters of arbitrary shapes and identifying outliers using density-based spatial clustering.

Probabilistic clustering using Expectation-Maximization and the Normal distribution.